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Everyday questions can be answered by any AI model. The complex, token-heavy work is where the competition lives. Tasha Keeney discusses with Brett Winton how much knowledge work is actually up for grabs to cheaper Chinese or open-source models on "The Brainstorm."

23,628 просмотров • 1 месяц назад •via X (Twitter)

Комментарии: 7

Фото профиля Jordan Blake
Jordan Blake1 месяц назад

@TashaARK @wintonARK Complex token-heavy knowledge work is the real battlefield. Open-source + Chinese model data is closing the gap fast.

Фото профиля Pickled Tink
Pickled Tink1 месяц назад

@TashaARK @wintonARK I asked grok a question yesterday. The answer wasn't what I was hearing from an employee. I verified before I accused the employee of anything. Grok was wrong. Beware. Grok gets information from online sources. GIGO.

Фото профиля MONEY MATRIX USA 💰
MONEY MATRIX USA 💰1 месяц назад

@TashaARK @wintonARK Energy is the real bottleneck here. AI and robotics can scale fast, but without a massive jump in cheap, reliable power the $100T opportunity stays theoretical. Curious how ARK models the energy constraint in the report.

Фото профиля Tony Floatana
Tony Floatana1 месяц назад

@TashaARK @wintonARK Commodity AI is 10,000 tickers fighting for the same bid. Token-heavy work is a two-name float, chico. Open source owns the volume. Frontier owns the supply. That spread already told you the trade.

Фото профиля Ansem 🐂🀄️
Ansem 🐂🀄️1 месяц назад

@TashaARK @wintonARK Sounds like a fascinating convo! Can't wait to hear their insights on the future of AI in knowledge work.

Фото профиля punkbrwstr
punkbrwstr1 месяц назад

@TashaARK @wintonARK ...or the guy whose costs are 10x higher is dead?

Фото профиля MONEY MATRIX USA 💰
MONEY MATRIX USA 💰1 месяц назад

@TashaARK @wintonARK Energy is the real bottleneck here. AI and robotics can scale fast, but without a massive jump in cheap, reliable power the $100T opportunity stays theoretical. Curious how ARK models the energy constraint in the report.

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OpenAI chairman Bret Taylor talks to about 100 CEOs every month. His answer to the cheap open-weight model panic: cheaper to train does not mean cheaper to use, and the number that decides it is token efficiency. "One thing that I think is a little bit overblown about these open weight models is they're not necessarily cheaper to run. Whether or not they're cheaper to train, you don't care. Because you're using just as many tokens. In fact, they may be less efficient." "There's this thing called token efficiency. And it turns out the frontier models are much, much more token efficient." "A token is to intelligence like a watt is to electricity... how many tokens does it take to complete a task? Not every token is actually equal." "For a lot of tasks, it turns out these frontier models from OpenAI and Anthropic are actually just better than these open weight models... just having open weights isn't actually the main thing driving any of those costs." Later in the same interview he goes after the billing unit itself: "It would be like if you signed up for Gmail and you paid for CPU cycle or something... where the world is going is paying for outcomes." The unresolved column: the chart CNBC airs mid-answer, from Artificial Analysis, prices a completed task at $0.94 on Kimi K3 against $2.75 on Claude Fable 5, efficiency folded in. If that gap holds, the premium he is defending gets earned on quality, not price. - Bret Taylor (Bret Taylor), OpenAI chairman and Sierra co-founder, on CNBC's Squawk Box.

Karl Mehta

17,254 просмотров • 1 месяц назад